Triple

T10428070
Position Surface form Disambiguated ID Type / Status
Subject Rygge E245836 entity
Predicate adjacentTo P224 FINISHED
Object Råde E245865 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Råde | Statement: [Rygge, adjacentTo, Råde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Råde
Context triple: [Rygge, adjacentTo, Råde]
  • A. Råde chosen
    Råde is a municipality in Viken county in southeastern Norway, known for its rural landscape and proximity to the city of Sarpsborg.
  • B. Rolde
    Rolde is a village in the Dutch province of Drenthe, known for its historic church and nearby prehistoric dolmens.
  • C. Rahden
    Rahden is a small town in North Rhine-Westphalia, Germany, known for its rural character and traditional Westphalian heritage.
  • D. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • E. Fagerborg
    Fagerborg is a residential neighborhood in Oslo, Norway, known for its central location, historic buildings, and proximity to major educational institutions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea4a7dcc81909a830e08656a1c0c completed April 7, 2026, 11:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fc2b50b48190b1d5b29d19a240c2 completed April 9, 2026, 7:21 p.m.
Created at: April 6, 2026, 12:13 p.m.